{"id":"W4312975163","doi":"10.1115/gt2022-79904","title":"Estimation of Autoignition Propensity in Aeroderivative Gas Turbine Premixers Using Incompletely Stirred Reactor Network Modelling","year":2022,"lang":"en","type":"article","venue":"","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Siemens (Canada)","funders":"","keywords":"Autoignition temperature; Computational fluid dynamics; Ignition system; Chemical reactor; Nuclear engineering; Computer science; Process engineering; Aerospace engineering; Engineering; Thermodynamics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002079548,0.0001006279,0.0001708655,0.0001002771,0.00006056858,0.00001058706,0.00006978562,0.00002899298,0.00007408568],"category_scores_gemma":[0.00001353362,0.0001151589,0.00002871663,0.0003777566,0.00001682299,0.0001358406,0.00006052078,0.000197973,8.273815e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629536,"about_ca_system_score_gemma":0.0000217676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001221922,"about_ca_topic_score_gemma":0.00003135936,"domain_scores_codex":[0.9992439,0.00004949736,0.0002782629,0.0001207449,0.0001573606,0.0001502565],"domain_scores_gemma":[0.9997295,0.00003910517,0.00005845459,0.0001142891,0.00003336036,0.00002527958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002708864,0.00002236045,0.000280895,0.00003036437,0.000009145733,0.000001463059,0.0003241472,0.9951234,0.002142124,0.0002584758,0.00004323171,0.001737327],"study_design_scores_gemma":[0.0002536822,0.00002231322,0.0006344216,0.00003239458,0.000007707474,0.000003554542,0.00009083107,0.9977252,0.000370265,0.0007196883,0.00001836192,0.0001216088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6069313,0.00001060657,0.3923203,0.00001305391,0.0001013223,0.0001812448,0.000007041649,0.000097131,0.0003380195],"genre_scores_gemma":[0.979286,0.000004340244,0.0205518,0.00001189208,0.00001567448,0.00001209423,0.00008315674,0.00001872811,0.00001634453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3723547,"threshold_uncertainty_score":0.4696045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04194855335687703,"score_gpt":0.2228253974347049,"score_spread":0.1808768440778279,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}